One serious problem faced by the banking industry is loss of funds due to fraudulent ATM transactions. One known technique used by the criminal is to install a fake card reader to steal magnetic swipe information of the ATM card, which is sometimes combined with attaching a small wireless camera to the surface of the ATM to steal the matching PIN code. The banking industry suffers tremendous loss due to such fraudulent transactions as often times the lost funds cannot be recovered.
Systems that try to detect general changes in the scene associated with an ATM are known. However, existing video systems that detect changes in the scene at an ATM and generate alerts in response to such changes do not detect specific domain-meaningful markers that annotate human actions. Nor do existing systems use such markers to select the reference scene model for detecting the type of changes required.